Fulltime Github Software Engineer Jobs in Nebraska

Position Overview

TAG is hiring Software Engineer to help design and deliver AI-powered enterprise applications across Kiewit's district portfolio. This role is ideal for a developer who has outgrown pure implementation and is ready to think at the systems level - shaping how applications are structured, how they integrate, and how AI can be leveraged to accelerate delivery. You'll work alongside senior architects while building your own architectural instincts through hands-on design and mentorship.

District Overview

Kiewit Technology Group (KTG) builds solutions to enable and support a $15 billion company. Our mission is to deliver project schedule and cost certainty by employing technology designed by and for the construction industry. Our team deploys technology solutions to the field and home office departments that increase profitability by maximizing the way we use our people and resources in daily operations, KTG uses systems and tools that manage every part of Kiewit's business and lifecycle of a project to improve planning and day-to0day execution in the field by giving our people real-time data to make faster, smarter decisions. When you join KTG, you will make an impact on the critical work we do every day.

Location

This is a full time in office role located on our LaVista, NE campus. 

Responsibilities

You'll build features and district-specific delivery projects - from front-end experiences to backend APIs and the infrastructure that supports them. You'll work with modern frameworks and AI-approved development tools, and partner closely with designers, product owners, and other engineers to ship high-quality software that Kiewit teams rely on every day.

As a Solutions Engineer you will help design, build, and optimize AI-systems and solutions that advance our digital capabilities and create real value for districts

Write clean, well-tested, maintainable code and contribute to a growing shared codebase

Participate in code reviews, architecture discussions, and sprint ceremonies

Contribute to AI-assisted development workflows using AI-approved tools such as Claude, GitHub Copilot, and custom tooling

Debug, troubleshoot, and improve performance of existing applications

Collaborate with product owners and designers to translate requirements into working software

Support cross-functional work across PAVE, SPEQ, MUSE, and district delivery projects

Help evolve engineering practices, tooling, and documentation as the team grows

What Makes This Role Unique

You will work across multiple high-impact platforms; not siloed to one product

Our team builds using AI-approved tools as part of our own development workflow (Claude Code, Figma MCP, automated spec-to-code pipelines)

You'll help shape engineering practices for a fast-growing, greenfield team

Direct access to architects, tech leads, and leadership - small team, big impact

Tech Stack

Frontend: React + TypeScript (Vite), MSAL.js, TanStack Query

Backend: Python (FastAPI) or .NET (ASP.NET Core 8+)

Infrastructure: Azure Container Apps, Bicep, GitHub Actions

AI/ML: Claude API, Azure AI Foundry, custom agent pipelines - all via AI-approved tooling

Tools: GitHub Enterprise, Figma, Postman, Cloudflare

Qualifications

Required Qualifications

• Bachelor's degree in Computer Science, Software Engineering, or related field

  1-3 years of professional software development experience (or equivalent project work)

  Experience with at least one modern web framework (React, Angular, Vue) and one backend language (Python or C#/.NET)

  Solid understanding of software engineering fundamentals: data structures, testing, debugging, and API design

  Experience with Git-based workflows and CI/CD pipelines

  Comfort working with AI-approved development tools (e.g., Claude, GitHub Copilot) as part of a modern engineering workflow

  Strong analytical thinking and attention to detail

  Preferred Qualifications

  Experience with Azure services (Container Apps, API Management, Key Vault)

  Familiarity with AI/ML concepts: prompt engineering, LLM integration, or agent-based workflows

  Experience with Infrastructure-as-Code (Bicep, Terraform) and GitHub Actions

  Exposure to AI agent frameworks (LangChain, AutoGen, Claude tool use, or custom agent pipelines)

  Background in construction technology, industrial systems, or related domains is a plus